VAST Challenge 2021

Here we present the tools developed in the context of MiniChallenge 2 of the VAST Challenge 2021, as well as higher-resolution images of what is presented in the challenge submission.

Getting things to work
- Activate CORS
- Allow mixed content
Tools
Higher-resolution versions of submitted images

Getting things to work

To get the tools to work, you will have to activate Cross-Origin Resource Sharing (CORS) and allow your browser to show mixed content from http and https sources.

The instructions below are for the Google Chrome browser.

Activate CORS

Install the CORS Unblock extension from the Chrome Web Store.

Allow mixed content

For each of the URLs mentioned below, add the URL in the “Allowed to show insecure content” section of the Chrome Preferences: Preferences => Privacy and security => Site settings => Additional content settings => Insecure content

Tools

Matching credit cards with loyalty cards:
- https://vast2021-corrmatrix.vercel.app/
  - Interactive correlation matrix between credit cards and loyalty cards.
- https://vast2021-cc2ly.vercel.app/
  - Bipartite graph of credit cards and loyalty cards.
GPS tracking:
- https://vast2021-gps.vercel.app/
  - Classify timepoints as moving/stationary/missing.
  - Annotate points of interest.
Match credit cards to cars:
- https://vast2021-gps2cc.vercel.app/
  - Find unknown transaction times.
  - Annotated POI type and homes.
Explore who was where with whom:
- https://vast2021-meetings.vercel.app/
  - Upset visualisation (JKU Visual Data Science Lab) + meeting timelines.
Additional tools:
- https://vast2021-cartrace.vercel.app/
- https://car-stops.vercel.app/
- https://vast2021-gps-activity.vercel.app/
  - Shows which (parts of) roads have similar activity patterns.

Higher-resolution versions of submitted images

Figure 1. The number of transactions per location
Figure 2. Transactions over time. Locations were grouped manually
Figure 3. The credit-to-loyalty card matching process
Figure 4. Credit-to-loyalty card price vector correlations
Figure 5. Relations between credit and loyalty cards
Figure 6. Price differences between credit and loyalty card transactions. Darker colors indicate more transactions
Figure 7. L6267 is used by both 6899 and 6691. On Saturday 11, there is a 10-minute gap between transactions at different locations
Figure 8. L3288 is used by 1286 and 9241. 1286 uses L3288 for lunches of around 50 Kr
Figure 9. Estimated transaction times
Figure 10. Stops of car 5 (colored bars) with transactions of credit cards 6691 and 6899. Transactions centered on a stop match in location and time. Transactions above the stops could not be matched to the stop. Tooltips provide details and give access to the (un)match button. The match all button accepts all shown possible matches
Figure 11. Stops of cars 22 and 28 with transactions of 1286 and 9241. The pink stop indicates a period of missing GPS signal. Places visited together are annotated
Figure 12. An example of incorrect Kronos Mart transaction time
Figure 13. Decision tree for GPS classification
Figure 14. Begin and end GPS positions of non-moving periods. Red lines indicate missing periods. Black arrows indicate the offset of car 28
Figure 15. Timeline of GPS activity for cars 1, 9, 28 and 107. Red indicates missing periods, black spikes indicate movement
Figure 16 (animated gif). Filling in periods of missing GPS data (animated gif). Transaction times could be used to estimate the deprature time in the missing period
Figure 17. Points of Interest, coloured by type and sized by the number of distinct visiting cars
Figure 18. The car-to-credit card matching process
Figure 19. Car-to-credit card matches
Figure 20. Matched credit cards of car 29
Figure 21. Surprise party of Lars Azada (2). Circles are an Upset visualization indicating which cars were present, color indicates households, black for 1-person households
Figure 22. Nightly guard-duty pattern of perimeter control personnel at executives’ homes
Figure 23. Elsa Orilla (7) and Brand Tempestad (33) regularly meet around lunch time for 2 hours at the Chostus Hotel
Figure 24. Hennie Osvaldo (21) regularly visits the household of Lidelse Dedos (14) and Birgitta Frentet (18) on Wednesday nights and Sundays
Figure 25. Nils Calixto (1) and Isak Baza (5) are regulars at Ouzeri Elian
Figure 26. Price-distributions per location
Figure 27. Activity of car 101 on Thursday 16 (animated gif). Repeated route: Stewart and Sons -> Nationwide Refinery -> Office -> Airport
Figure 28. Activity of car 104 on Thursday 16 (animated gif). Repeated route: Office -> Airport
Figure 29. Activity of car 105 on Thursday 16 (animated gif). Repeating route: Office -> Carlyle Chemical Inc. -> Office -> Katerina’s Café
Figure 30. Activity of car 106 on Thursday 16 (animated gif). Repeating route: Scrapyard -> Stewart and Sons Fabrication -> Office -> Airport
Figure 31. Nils Calixto (1) goes to the office at night on multiple occasions
Figure 32. Ingrid Barranco (4), Ada Campo-Corrente (10), and Willem Vasco-Pais (35) play golf together. One week later Orhan Strum (32) and Sten Sanjorge Jr. (31) are also present
Figure 33. CEO Sten Sanjorge Jr. (31) eats with security personnel at Guy’s Gyros on Sunday 19
Figure 34. Ada Campo-Corrente (10), Orhan Strum (32), and Willem Vaco-Pais (35) eat with engineering personnel at Hippokampos